Image-Text-to-Text
MLX
Safetensors
qwen3_5
optiq
vision
vlm
lora
chartqa
apple-silicon
conversational
4-bit precision
Instructions to use mlx-community/chartreader-0.8B-OptiQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/chartreader-0.8B-OptiQ-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/chartreader-0.8B-OptiQ-4bit") config = load_config("mlx-community/chartreader-0.8B-OptiQ-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use mlx-community/chartreader-0.8B-OptiQ-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/chartreader-0.8B-OptiQ-4bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mlx-community/chartreader-0.8B-OptiQ-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/chartreader-0.8B-OptiQ-4bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/chartreader-0.8B-OptiQ-4bit"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default mlx-community/chartreader-0.8B-OptiQ-4bit
Run Hermes
hermes
- OpenClaw new
How to use mlx-community/chartreader-0.8B-OptiQ-4bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/chartreader-0.8B-OptiQ-4bit"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "mlx-community/chartreader-0.8B-OptiQ-4bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
| { | |
| "base_model": "/Users/asankhaya/.cache/huggingface/hub/models--mlx-community--Qwen3.5-0.8B-OptiQ-4bit/snapshots/a1207d2d46c30448362eb41aab04068c7e7eea6d", | |
| "fine_tune_type": "lora", | |
| "model_type": "qwen3_5", | |
| "vlm": true, | |
| "lora_parameters": { | |
| "rank": 8, | |
| "scale": 8.0, | |
| "dropout": 0.0, | |
| "keys": [ | |
| "self_attn.q_proj", | |
| "self_attn.k_proj", | |
| "self_attn.v_proj", | |
| "self_attn.o_proj", | |
| "mlp.gate_proj", | |
| "mlp.up_proj", | |
| "mlp.down_proj" | |
| ] | |
| } | |
| } |